Top Remote Data & Analytics Jobs in Albuquerque, NM

Design, build, and maintain scalable batch and near-real-time data pipelines and data products using Databricks and Spark. Integrate internal/external sources, implement data models, ensure data quality, support BI (Sisense), CI/CD, and collaborate with analysts, scientists, and stakeholders to enable analytics and decision-making.

The Senior Clinical Research Associate manages site monitoring and relationships for clinical trials, ensuring compliance and patient safety according to GCP and regulations.

Leads a team delivering Customer Success reporting, dashboards, KPI frameworks, and operational analytics. Oversees reporting accuracy, data integrity, recurring metrics, workflow improvements, and automation. Partners with Customer Success and services leadership to translate business needs into analytical requirements, prioritize initiatives, standardize reporting methodologies, and communicate performance insights. Coaches analysts, manages workload and development, and supports data-driven operational decision-making and scaling.

Leads internal data analysis projects, identifies business opportunities and risks, delivers strategic insights to leadership, manages junior analysts, develops dashboards, and improves data quality across company platforms. The role requires translating quantitative findings for nontechnical audiences and applying healthcare or pharmaceutical dataset experience to strategic decision-making.

The Salesforce Data Architect will lead complex data migration initiatives, ensuring data quality and governance while collaborating with stakeholders to implement scalable Salesforce solutions.

The Senior Data Engineer will design and scale cloud-based data platforms, ensuring quality and performance while collaborating with cross-functional teams to deliver actionable data solutions.

Lead study design, survey development, questionnaire quality, data analysis, and client-ready reporting for financial services research. Interpret findings with client teams, translate results into actionable business insights, apply analytical methods, and ensure accuracy, clarity, timeliness, and integrity across multiple projects.

Leads complex, enterprise-scale data engineering initiatives using Databricks and Azure. Designs and implements scalable lakehouse architectures, high-performance pipelines, and platform capabilities while establishing engineering standards for reliability, security, observability, and cost efficiency. Mentors engineers, leads through influence, embeds across teams to accelerate delivery, manages technical risks, and advises stakeholders on data strategies and architectural trade-offs. Collaborates with Architecture, Platform, AI, Analytics, Security, and Governance teams.

Design, operate, and scale end-to-end data infrastructure and pipelines. Build reusable data models and a semantic layer, ensure data quality and privacy, implement observability and SLAs, support marketing and growth feeds, partner with cross-functional stakeholders, and enable ML/AI consumption and reverse ETL workflows.

Designs and maintains healthcare data pipelines, ETL workflows, databases, data models, and analytical frameworks. Analyzes claims and payer data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders and collaborates with healthcare policy experts, analysts, and other stakeholders to translate requirements into data solutions. The role also improves data infrastructure and analytics capabilities.